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  1. 1.7. Gaussian Processes — scikit-learn 1....

    1.7.3. GPC examples # 1.7.3.1. Probabilistic predictions...features exceeds a few dozens. 1.7.1. Gaussian Process Regression...
    scikit-learn.org/stable/modules/gaussian_process.html
    Mon Jan 26 11:09:14 GMT 2026
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  2. make_hastie_10_2 — scikit-learn 1.8.0 doc...

    float64(-1.0), np.float64(1.0), np.float64(-1.0), np.float64(1.0),...i ] = 1 if np . sum ( X [ i ] ** 2 ) > 9.34 else - 1 Read more...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.make_hastie_10_2.html
    Mon Jan 26 11:09:12 GMT 2026
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  3. Matern — scikit-learn 1.8.0 documentation

    kernel = 1.0 * Matern ( length_scale = 1.0 , nu = 1.5 ) >>>...length_scale = 1.0 , length_scale_bounds = (1e-05, 100000.0) , nu = 1.5 )...
    scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Matern.html
    Mon Jan 26 14:16:29 GMT 2026
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  4. binarize — scikit-learn 1.8.0 documentation

    1., 0.], [1., 0., 0.]]) On this page...are replaced by 0, above it by 1. Threshold may not be less than...
    scikit-learn.org/stable/modules/generated/sklearn.preprocessing.binarize.html
    Mon Jan 26 14:16:33 GMT 2026
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  5. silhouette_score — scikit-learn 1.8.0 doc...

    The best value is 1 and the worst value is -1. Values near 0 indicate...<= n_labels <= n_samples - 1 . This function returns the mean...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html
    Mon Jan 26 14:16:29 GMT 2026
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  6. SVM Tie Breaking Example — scikit-learn 1...

    1 ] . min (), X [:, 1 ] . max ()] xs = np...xlim [ 1 ], 1000 ) ys = np . linspace ( ylim [ 0 ], ylim [ 1 ], 1000...
    scikit-learn.org/stable/auto_examples/svm/plot_svm_tie_breaking.html
    Mon Jan 26 11:09:17 GMT 2026
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  7. inplace_csr_column_scale — scikit-learn 1...

    1 , 2 , 2 ]) >>> data = np . array ([ 8 , 1 , 2...csr . todense () matrix([[8, 1, 2], [0, 0, 5], [0, 0, 0], [0,...
    scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.inplace_csr_column_scale.html
    Mon Jan 26 14:16:30 GMT 2026
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  8. KMeans — scikit-learn 1.8.0 documentation

    scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Clustering...X = np . array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 10 , 2...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html
    Mon Jan 26 11:09:12 GMT 2026
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  9. Understanding the decision tree structure &#821...

    [{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...[{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...
    scikit-learn.org/stable/auto_examples/tree/plot_unveil_tree_structure.html
    Mon Jan 26 11:09:12 GMT 2026
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  10. make_gaussian_quantiles — scikit-learn 1....

    dataset is from Zhu et al [1] . References [ 1 ] J. Zhu, H. Zou, S....es ( * , mean = None , cov = 1.0 , n_samples = 100 , n_features...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.make_gaussian_quantiles.html
    Mon Jan 26 14:16:33 GMT 2026
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